Chronic obstructive pulmonary disease (COPD) and bronchial asthma (BA) are the most common non-communicable lung diseases with significant socioeconomic impacts.

The MHH cooperates in the joint project CALM-QE with twelve university institutions as well as five associated partners such as COPD Deutschland e.V. The aim of the project is to be able to better diagnose and individually treat patients with BA and COPD. Together with the Clinic for Pediatric Pneumology, Allergology and Neonatology of the Hannover Medical School, the influencing factors of the disease patterns and their interactions are to be better understood. With the help of the infrastructure created between the university hospitals, the exchange of medical data will be simplified. The prerequisites and necessary measures for the interoperability and exchangeability of data are therefore coordinated across the institutions.

For the identification and grouping of disease processes, data are obtained from various sources. This involves the integration of local climate and air pollution data as well as biosignals obtained from wearables. Furthermore, data from research studies are included, among them longitudinal data from the German COPD cohort. Machine learning and artificial intelligence techniques will be used to develop multidimensional predictive models for multiple clinically relevant outcome parameters to predict risk for key clinical outcome parameters. The newly gained knowledge will contribute to a qualitative improvement in the health care of COPD and BA.